{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:VT7N53BK4CBM5DSVE3FEGP6GNV","short_pith_number":"pith:VT7N53BK","canonical_record":{"source":{"id":"1606.05572","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-06-17T15:58:24Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"f279adc230a0b1251a69004fe41191c59d2b3cf70f3985506f5d2c6d83ab3dc9","abstract_canon_sha256":"f3234d9fd733b8da287a669437d2f682d731b8f2e065fd74af636ca331b3d0f8"},"schema_version":"1.0"},"canonical_sha256":"acfedeec2ae082ce8e5526ca433fc66d54f695f4b1f1e43bd0b36f9ab89de012","source":{"kind":"arxiv","id":"1606.05572","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1606.05572","created_at":"2026-05-18T01:12:19Z"},{"alias_kind":"arxiv_version","alias_value":"1606.05572v1","created_at":"2026-05-18T01:12:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1606.05572","created_at":"2026-05-18T01:12:19Z"},{"alias_kind":"pith_short_12","alias_value":"VT7N53BK4CBM","created_at":"2026-05-18T12:30:48Z"},{"alias_kind":"pith_short_16","alias_value":"VT7N53BK4CBM5DSV","created_at":"2026-05-18T12:30:48Z"},{"alias_kind":"pith_short_8","alias_value":"VT7N53BK","created_at":"2026-05-18T12:30:48Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:VT7N53BK4CBM5DSVE3FEGP6GNV","target":"record","payload":{"canonical_record":{"source":{"id":"1606.05572","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-06-17T15:58:24Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"f279adc230a0b1251a69004fe41191c59d2b3cf70f3985506f5d2c6d83ab3dc9","abstract_canon_sha256":"f3234d9fd733b8da287a669437d2f682d731b8f2e065fd74af636ca331b3d0f8"},"schema_version":"1.0"},"canonical_sha256":"acfedeec2ae082ce8e5526ca433fc66d54f695f4b1f1e43bd0b36f9ab89de012","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:12:19.380475Z","signature_b64":"EsXpMFPK9d/AyeGm5kZBtFvW/ST8Vzmxc6Xf1INb4h2d3bkoft7vt6fq41lPJMEbeXx5aoYALzuzHQGT2yN3AA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"acfedeec2ae082ce8e5526ca433fc66d54f695f4b1f1e43bd0b36f9ab89de012","last_reissued_at":"2026-05-18T01:12:19.380113Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:12:19.380113Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1606.05572","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T01:12:19Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HzYc84dwM26PJWX78F7inSQZNIKe2WWdhWbS6ZaDP0OgC3dn9b/JTyYXT+hpIMIs81n9uT3fMoqYSPUcxfqCCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T18:23:17.200670Z"},"content_sha256":"5014bb0ac10b289fdee4a20353f4f31eca9420243f053196444f7d9e99a9f1b6","schema_version":"1.0","event_id":"sha256:5014bb0ac10b289fdee4a20353f4f31eca9420243f053196444f7d9e99a9f1b6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:VT7N53BK4CBM5DSVE3FEGP6GNV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning Interpretable Musical Compositional Rules and Traces","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Guy E. Garnett, Haizi Yu, Lav R. Varshney, Ranjitha Kumar","submitted_at":"2016-06-17T15:58:24Z","abstract_excerpt":"Throughout music history, theorists have identified and documented interpretable rules that capture the decisions of composers. This paper asks, \"Can a machine behave like a music theorist?\" It presents MUS-ROVER, a self-learning system for automatically discovering rules from symbolic music. MUS-ROVER performs feature learning via $n$-gram models to extract compositional rules --- statistical patterns over the resulting features. We evaluate MUS-ROVER on Bach's (SATB) chorales, demonstrating that it can recover known rules, as well as identify new, characteristic patterns for further study. W"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1606.05572","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T01:12:19Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aBWQOnKp8Du5W8ioAbk06quJf+rXSm584y47UVl9EdLxIJf8uXReNPL3VYAxzjsC1eoBOcXtWkmjGbKyAgH+CQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T18:23:17.201007Z"},"content_sha256":"ad4699ca5d10a9bb8526b725b39fe4d5770cc3b3f420b459eed9d4a6c0f810a2","schema_version":"1.0","event_id":"sha256:ad4699ca5d10a9bb8526b725b39fe4d5770cc3b3f420b459eed9d4a6c0f810a2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VT7N53BK4CBM5DSVE3FEGP6GNV/bundle.json","state_url":"https://pith.science/pith/VT7N53BK4CBM5DSVE3FEGP6GNV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VT7N53BK4CBM5DSVE3FEGP6GNV/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-03T18:23:17Z","links":{"resolver":"https://pith.science/pith/VT7N53BK4CBM5DSVE3FEGP6GNV","bundle":"https://pith.science/pith/VT7N53BK4CBM5DSVE3FEGP6GNV/bundle.json","state":"https://pith.science/pith/VT7N53BK4CBM5DSVE3FEGP6GNV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VT7N53BK4CBM5DSVE3FEGP6GNV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:VT7N53BK4CBM5DSVE3FEGP6GNV","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"f3234d9fd733b8da287a669437d2f682d731b8f2e065fd74af636ca331b3d0f8","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-06-17T15:58:24Z","title_canon_sha256":"f279adc230a0b1251a69004fe41191c59d2b3cf70f3985506f5d2c6d83ab3dc9"},"schema_version":"1.0","source":{"id":"1606.05572","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1606.05572","created_at":"2026-05-18T01:12:19Z"},{"alias_kind":"arxiv_version","alias_value":"1606.05572v1","created_at":"2026-05-18T01:12:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1606.05572","created_at":"2026-05-18T01:12:19Z"},{"alias_kind":"pith_short_12","alias_value":"VT7N53BK4CBM","created_at":"2026-05-18T12:30:48Z"},{"alias_kind":"pith_short_16","alias_value":"VT7N53BK4CBM5DSV","created_at":"2026-05-18T12:30:48Z"},{"alias_kind":"pith_short_8","alias_value":"VT7N53BK","created_at":"2026-05-18T12:30:48Z"}],"graph_snapshots":[{"event_id":"sha256:ad4699ca5d10a9bb8526b725b39fe4d5770cc3b3f420b459eed9d4a6c0f810a2","target":"graph","created_at":"2026-05-18T01:12:19Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"Throughout music history, theorists have identified and documented interpretable rules that capture the decisions of composers. This paper asks, \"Can a machine behave like a music theorist?\" It presents MUS-ROVER, a self-learning system for automatically discovering rules from symbolic music. MUS-ROVER performs feature learning via $n$-gram models to extract compositional rules --- statistical patterns over the resulting features. We evaluate MUS-ROVER on Bach's (SATB) chorales, demonstrating that it can recover known rules, as well as identify new, characteristic patterns for further study. W","authors_text":"Guy E. Garnett, Haizi Yu, Lav R. Varshney, Ranjitha Kumar","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-06-17T15:58:24Z","title":"Learning Interpretable Musical Compositional Rules and Traces"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1606.05572","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:5014bb0ac10b289fdee4a20353f4f31eca9420243f053196444f7d9e99a9f1b6","target":"record","created_at":"2026-05-18T01:12:19Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"f3234d9fd733b8da287a669437d2f682d731b8f2e065fd74af636ca331b3d0f8","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-06-17T15:58:24Z","title_canon_sha256":"f279adc230a0b1251a69004fe41191c59d2b3cf70f3985506f5d2c6d83ab3dc9"},"schema_version":"1.0","source":{"id":"1606.05572","kind":"arxiv","version":1}},"canonical_sha256":"acfedeec2ae082ce8e5526ca433fc66d54f695f4b1f1e43bd0b36f9ab89de012","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"acfedeec2ae082ce8e5526ca433fc66d54f695f4b1f1e43bd0b36f9ab89de012","first_computed_at":"2026-05-18T01:12:19.380113Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:12:19.380113Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"EsXpMFPK9d/AyeGm5kZBtFvW/ST8Vzmxc6Xf1INb4h2d3bkoft7vt6fq41lPJMEbeXx5aoYALzuzHQGT2yN3AA==","signature_status":"signed_v1","signed_at":"2026-05-18T01:12:19.380475Z","signed_message":"canonical_sha256_bytes"},"source_id":"1606.05572","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5014bb0ac10b289fdee4a20353f4f31eca9420243f053196444f7d9e99a9f1b6","sha256:ad4699ca5d10a9bb8526b725b39fe4d5770cc3b3f420b459eed9d4a6c0f810a2"],"state_sha256":"4e752acfd4abe41fa14ef0f82af077515565f1dda36950f10482abc92eee22e4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bMH8vm3omcNk28s4veFwkYwASSyjUoxwggR6cEGLtn8vmSCxqdAo6RC5An4vnqbPgZ2sEX/zSELs+R3MVhvgDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-03T18:23:17.202903Z","bundle_sha256":"08c47f1b5221712f7d7dec26d229bc1f7c60a0f585a900c976bf7433842251c7"}}